Deep Learning for Medical Image Analysis with MATLAB

Event Type Start Time End Time
Webex 1 Jun 2021 - 10:00 CEST 1 Jun 2021 - 11:00 CEST


Deep Learning enables remarkable advancements in the medical imaging field. This type of automated algorithm helps in providing a valuable second opinion to the healthcare professionals during the screening process. Deep Learning using MATLAB helps in quickly prototyping and developing algorithms. More recently, Dr. Narayanan applied a Deep Learning based technique for detecting COVID-19 on Chest Radiographs using MATLAB and he states, "MATLAB was instrumental in developing an algorithm for rapid detection of COVID-19 on chest radiographs using a limited set of training images".

Join this webinar to discover how to apply Deep Learning in practice with MATLAB to build robust medical imaging applications. We will use detailed examples to show how MATLAB can facilitate the design, research, fine-tuning and thorough testing of Deep Learning techniques.


  • Easily manage large image dataset using datastores
  • Interactively use apps to semi-automate the process of generating ground-truth labels from images
  • Efficiently train and evaluate a semantic segmentation model using labelled images
  • Automatically generate optimized code to deploy on a medical device

Who Should Attend

  • Software and hardware engineers
  • Researchers
  • Data scientists
  • Innovation leaders
  • Project managers and technical managers

About the Presenter

Paola Jaramillo is an application engineer at MathWorks in Eindhoven, The Netherlands. She specializes in signal and image processing, computer vision, and machine learning. Her primary interests are sensor data analytics and autonomous systems. Prior to joining MathWorks she worked as a researcher on the fields of machine learning and signal processing for intelligent lighting systems at the Eindhoven University of Technology. Paola holds a Masters in Electronic Engineering from Politecnico di Torino (Italy) and carried out a six-month internship in the area of Structural Health Monitoring at IBM Zurich Research Laboratories in Switzerland.

Mauro Fusco is an application engineer at MathWorks in Eindhoven. He specializes in supporting customers in aerospace, automotive and machinery industries for the establishment of Design Automation workflows. Modelling, simulation, testing and implementation through automatic code generation whilst conforming to international standards are key aspects of his work. He is currently working on transferring this knowledge into the medical Industry for safety critical applications.

Before joining MathWorks, he worked at the Dutch Organization for Applied Research, TNO, focusing on the domain of Controls for Cooperative and Autonomous Driving. Mauro has a Masters in Automation Engineering from the University of Naples Federico II, during which time he conducted research at Eindhoven University of Technology. His technical expertise lies in the areas of Control Theory, Nonlinear and Network Control and their implementation.

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